Data compression is being pervasively used in data storage and communication systems to reduce the cost and/or improve speed performance. A large number of data compression algorithms exist today, spanning a wide spectrum on the trade-off between data compression ratio and data processing complexity. Higher data processing complexity tends to cause slower compression/decompression throughput. Entropy coding is a lossless data compression scheme that is one of the most important components in virtually every data compression system, and Huffman coding is the most common entropy coding techniques being used in practice. However, such entropy coding techniques generally utilize sorting or the like that requires serial processing, which can be slow. Given the industry acceptance of entropy coding, it is highly desirable to minimize the implementation complexity of entropy based encoding systems.